The following account of the prior art relates to one of the areas of application of the present application, hearing aids.
Acoustic feedback occurs because the output loudspeaker signal from an audio system providing amplification of a signal picked up by a microphone is partly returned to the microphone via an acoustic coupling through the air or other media. The part of the loudspeaker signal returned to the microphone is then re-amplified by the system before it is re-presented at the loudspeaker, and again returned to the microphone. As this cycle continues, the effect of acoustic feedback becomes audible as artefacts or even worse, howling, when the system becomes unstable. The problem appears typically when the microphone and the loudspeaker are placed closely together, as e.g. in hearing aids or other audio systems. Some other classic situations with feedback problems are telephony, public address systems, headsets, audio conference systems, car audio systems, etc. Unstable systems due to acoustic feedback tend to significantly contaminate the desired audio input signal with narrow band frequency components, which are often perceived as howl or whistle. A variety of feedback cancellation methods have been described to increase the stability of an audio processing system. The feedback path of an audio processing device, e.g. a listening device, e.g. a hearing aid, may vary over time. Adaptive feedback cancellation has the ability to track feedback path changes over time and is e.g. based on an adaptive filter comprising a linear time invariant filter (variable filter part of the adaptive filter) to estimate the feedback path, and wherein its filter weights are updated over time (e.g. calculated in an update (algorithm) part of the adaptive filter). The filter update may be calculated using stochastic gradient algorithms, including some form of the Least Mean Square (LMS) or the Normalized LMS (NLMS) algorithms. A drawback of these methods is that the estimate of the acoustic feedback path (provided by the adaptive filter) will be biased, if the input signal to the system is not white (i.e. if there is autocorrelation) because the estimate is made in a ‘closed loop’. This means that the anti feedback system may introduce artefacts when there is autocorrelation (e.g. tones) in the input. ‘Open loop’ estimation is possible, as e.g. described in EP 2 237 573 A1.
The algorithm part of the adaptive filter comprises an adaptive algorithm for calculating updated filter coefficients for being transferred to the variable filter part of the adaptive filter. The timing of calculation and/or the transfer of updated filter coefficients from the algorithm part to the variable filter part may be controlled by an update control unit. The timing of the update (e.g. its specific point in time, and/or its update frequency) may preferably be influenced by various properties of the signal of the forward path. The control scheme may preferably be supported by various sensors of the audio processing device, e.g. a feedback detector (e.g. comprising a tone detector) for detecting whether a given frequency component is likely to be due to feedback or to be inherent in the externally originating part of the input signal (e.g. music). The timing of the adaptive algorithm for calculation and updating filter coefficients (e.g. the time interval between each calculation/update) may be defined by an adaptation rate, which again may be controlled by a step size of the adaptive algorithm.
U.S. Pat. No. 7,106,871 describes a method for canceling feedback in an acoustic system compromising a microphone, a signal path, a speaker and means for detecting presence of feedback between the speaker and the microphone, the method comprising providing a LMS algorithm for processing the signal; where the LMS algorithm operates with a predetermined adaptation speed when feedback is not present; where the LMS algorithm operates an adaptation speed faster than the predetermined adaptation speed when feedback is present, and where the means for detecting the presence of feedback is used to control the adaptation speed selection of the LMS algorithm.
WO 2007/113282 A1 describes a hearing aid comprising an adaptive feedback cancellation filter for adaptively deriving a feedback cancellation signal from a processor output signal by applying filter coefficients, and calculation means for calculating the autocorrelation of a reference signal, and an adaptation means for adjusting the filter coefficients with an adaptation rate, wherein the adaptation rate is controlled in dependency of the autocorrelation of the reference signal.
[Ma et al.; 2011] deals with feedback suppression, in particular adaptive feedback cancellation, which uses an adaptive filter to estimate the feedback path. However, a large modeling error and a cancellation of the desired signal may occur when the external input signal is correlated with the receiver input signal. It is proposed to replace the hearing-aid output with a synthesized signal, which sounds perceptually the same as or similar to the original signal but is statistically uncorrelated with the external input signal at high frequencies where feedback oscillation usually occurs.
WO 2009/124550 A1 describes an audio system comprising a signal processor for processing an audio signal, and a feedback suppressor circuit configured for modelling a feedback signal path of the audio system by provision of a feedback compensation signal based on sets of feedback model parameters for the feedback signal path that are stored in a repository for storage of the sets of feedback model parameters.